张建军，华南农业大学数学与信息学院（软件学院）首聘副教授，硕士生导师，华南理工大学博士、博士后，主要从事机器学习、深度网络、不平衡数据流学习、医学图像分析等相关领域的研究，已发表学术论文40余篇，其中包括IEEE Transactions on Neural Networks and Learning Systems、IEEE Transactions on Cybernetics、IEEE Transactions on Industrial Informatics、IEEE Transactions on Medical Imaging、IEEE Journal of Biomedical and Health Informatics 等国际顶级期刊论文，ICASSP、SMC、IJCNN 等国际顶级会议论文。主持国家自然科学基金青年项目、广东省自然科学基金面上项目、广东省区域联合项目青年基金、广州市基础与应用基础研究项目，参与多项国家自然科学基金项目。目前担任IEEE TNNLS、IEEE TCYB、Machine Learning 等国际顶级期刊的审稿人。

指导21级本科生邓同学本科期间发表中科院1区Top期刊论文1篇，CCF-B类会议论文1篇，EI检索会议论文1篇，主持大学生创新创业训练计划项目1项，目前于美国藤校攻读博士学位。其它本科生或研究生同学在课题组期间均发表至少EI检索会议论文1篇或SCI期刊论文1篇。

· 2024-01至今，华南农业大学，数学与信息学院，首聘副教授

· 2021-01至2024-01，华南理工大学，计算机科学与工程学院，博士后，合作导师：陈俊龙 教授（IEEE Fellow，欧洲科学院院士，欧洲科学与艺术院院士）

· 2015-09至2020-12，华南理工大学，计算机科学与工程学院，博士，导师：吴永贤 教授（IEEE Senior Member）

· 2019-10至2020-10，加拿大阿尔伯塔大学，电气与计算机工程学院，联合培养博士，导师：Witold Pedrycz 教授（IEEE Fellow，加拿大皇家科学院院士，波兰科学院院士）

· 2011-09至2015-06，华南理工大学，计算机科学与工程学院，学士

7. 国家自然科学基金面上项目，基于局部泛化误差模型的高泛化图神经网络训练框架，参与

6. 国家自然科学基金青年项目，基于集成学习的多模态不平衡数据分类关键技术研究，主持

5. 广东省自然科学基金面上项目，面向高维带噪类别不平衡数据的鲁棒分类方法研究，主持

4. 广东省区域联合基金青年基金项目，基于集成学习的噪声不平衡数据分类关键技术研究，主持

3. 广州市基础与应用基础研究项目，基于局部泛化误差模型的人类行为识别基础理论与应用研究，主持

2. 国家自然科学基金面上项目，动态深度与宽度神经网络的泛化误差模型，参与

1. 广州市科技计划项目，基于动态哈希的视频人物追踪研究，参与

期刊论文（*通讯作者）

[22] Y. Liang, W. Tang, J. Zhang(张建军), T. Wang, W. W. Y. Ng, S. Chen, K. Jiang, X. Wei, X. Jiang, and Y. Guo, "XRadNet: A Radiomics-Guided Breast Cancer Molecular Subtype Prediction Network with a Radiomics Explanation," IEEE Journal of Biomedical and Health Informatics (中科院1区top, IF: 6.7), Accepted, 2025.

[21] L. Zhao, W. W. Y. Ng, J. Zhang*(张建军), and X. Wu, "An Innovative Multisource Teacher Collaborative Framework for Self-Knowledge Distillation," IEEE Transactions on Neural Networks and Learning Systems (中科院1区top, IF: 10.4), Accepted, 2025.

[20] W. Li, W. W. Y. Ng, H. Wang, J. Zhang*(张建军), and C. Zhong, "ERMAV: Efficient and Robust Graph Contrastive Learning via Multi-Adversarial Views Training," IEEE Transactions on Cybernetics (中科院1区top, IF: 11.8), Accepted, 2025.

[19] W. Li, W. W. Y. Ng, H. Wang, J. Zhang(张建军), and C. Zhong, "Robust Graph Representation Learning with Asymmetric Debiased Contrasts," Expert Systems with Applications (中科院1区top, IF: 7.5), accepted, 2024.

[18] X. Zhang, J. Chen, Q. Li, J. Zhang*(张建军), W. W. Y. Ng, and T. Wang, "LSSMSD: defending against black-box DNN model stealing based on localized stochastic sensitivity," International Journal of Machine Learning and Cybernetics (中科院3区, IF: 5.6), Early Access, 2024.

[17] S. Liu, X. Ma, S. Deng, Y. Suo, J. Zhang*(张建军), and W. W. Y. Ng, "Lightweight multimodal Cycle-Attention Transformer towards cancer diagnosis," Expert Systems with Applications (中科院1区top, IF: 7.5), vol. 255(B), article no. 124616, 2024.

[16] W. W. Y. Ng, Q. Zhang, C. Zhong, and J. Zhang*(张建军), "Improving domain generalization by hybrid domain attention and localized maximum sensitivity," Neural Networks (中科院1区top, IF: 7.8), vol. 171, pp. 320-331, 2024.

[15] J. Zhang(张建军), T. Wang, W. W. Y. Ng, and W. Pedrycz, "KNNENS: A k-nearest neighbor ensemble-based method for incremental learning under data stream with emerging new classes," IEEE Transactions on Neural Networks and Learning Systems (中科院1区top, IF: 10.4), vol. 34, no. 11, 2023.

[14] T. Wang, S. Lu, J. Zhang*(张建军), X. Liu, X. Tian, W. W. Y. Ng, and W. Chen, "SBHA: Sensitive binary hashing autoencoder for image retrieval," IEEE Transactions on Cybernetics (中科院1区top, IF: 11.8), Early Access, 2023.

[13] X. Zhang, C. Zhong, J. Zhang*(张建军), T. Wang, and W. W. Y. Ng, "Robust recurrent neural networks for time series forecasting," Neurocomputing (中科院2区top, IF: 6), vol. 526, pp. 143-157, 2023.

[12] W. W. Y. Ng, S. Xu, J. Zhang*(张建军), X. Tian, T. Rong and S. Kwong, "Hashing-based undersampling ensemble for imbalanced pattern classification problems," IEEE Transactions on Cybernetics (中科院1区top, IF: 11.8), vol. 52, no. 2, pp. 1269-1279, Feb. 2022.

[11] T. Wang, M. Zhang, J. Zhang*(张建军), W. W. Y. Ng, and C. L. P. Chen, "BASS: Broad network based on localized stochastic sensitivity," IEEE Transactions on Neural Networks and Learning Systems (中科院1区top, IF: 10.4), Early Access, 2022.

[10] J. Zhang(张建军), T. Wang, W. W. Y. Ng, and W. Pedrycz, "Ensembling perturbation-based oversamplers for imbalanced datasets," Neurocomputing (中科院2区top, IF: 6), vol. 479, pp. 1-11, 2022.

[9] J. Zhang(张建军), T. Wang, W. W. Y. Ng, and W. Pedrycz, "Perturbation-based oversampling technique for imbalanced classification problems," International Journal of Machine Learning and Cybernetics (中科院3区, IF: 5.6), vol. 14, no. 3, pp. 1-15, 2022.

[8] W. W. Y. Ng, Z. Liu, J. Zhang*(张建军), and W. Pedrycz, "Maximizing minority accuracy for imbalanced pattern classification problems using cost-sensitive localized generalization error model," Applied Soft Computing (中科院2区top, IF: 8.7), vol. 104, no. 5, article no. 107178, 2021.

[7] C. S. Lai, Y. Yang, K. Pan, J. Zhang(张建军), H. L. Yuan, W. W. Y. Ng, Y. Gao, Z. Zhao, T. Wang, M. Shahidehpour, and L. L. Lai, "Multi-view neural network ensemble for short and mid-term load forecasting," IEEE Transactions on Power Systems (中科院1区top, IF: 6.6), vol. 36, no. 4, pp. 2992-3003, 2021.

[6] W. W. Y. Ng, Y. Tuo, J. Zhang*(张建军), and S. Kwong, "Training error and sensitivity-based ensemble feature selection," International Journal of Machine Learning and Cybernetics (中科院3区, IF: 5.6), vol. 11, pp. 2313-2326, 2020.

[5] J. Zhang(张建军), X. Chen, W. W. Y. Ng, C. S. Lai, and L. L. Lai, "New appliance detection for nonintrusive load monitoring," IEEE Transactions on Industrial Informatics (中科院1区top, IF: 12.3), vol. 15, no. 8, pp. 4819-4829, Aug. 2019.

[4] W. W. Y. Ng, J. Zhang(张建军), C. S. Lai, W. Pedrycz, L. L. Lai, and X. Wang, "Cost-sensitive weighting and imbalance-reversed bagging for streaming imbalanced and concept drifting in electricity pricing classification," IEEE Transactions on Industrial Informatics (中科院1区top, IF: 12.3), vol. 15, no. 3, pp. 1588-1597, March 2019.

[3] W. W. Y. Ng, Y. Zhang, J. Zhang*(张建军), D. D. Wang, and F. L. Wang, "Stochastic sensitivity tree boosting for imbalanced prediction problems of protein-ligand interaction sites," IEEE Transactions on Emerging Topics in Computational Intelligence (中科院2区, IF: 5.3), 2019.

[2] S. Zhang, W. W. Y. Ng, J. Zhang(张建军), C. D. Nugent, N. Irvine, and T. Wang, "Evaluation of radial basis function neural network minimizing L-GEM for sensor-based activity recognition," Journal of Ambient Intelligence and Humanized Computing (中科院3区), vol. 14, pp. 53-63, 2019.

[1] W. W. Y. Ng, G. Zeng, J. Zhang*(张建军), D. S. Yeung, and W. Pedrycz, "Dual autoencoders features for imbalance classification problem," Pattern Recognition (中科院1区Top，IF: 8), vol. 60, no. 1, pp. 875-889, 2016.

会议论文

[19] X. Yang, S. Deng, S. Liu, Y. Suo, W. W. Y. Ng, J. Zhang*(张建军), "A Mathematics Framework of Artificial Shifted Population Risk and Its Further Understanding Related to Consistency Regularization," ECML PKDD (CCF-B类会议), pp. 73-88, 2024.

[18] X. Zhang, C. S. Lai, W. W. Y. Ng, S. Xu, X. Wu, J. Zhang(张建军), K. Pan, T. Wang, and Z. Zhao, "A Probabilistic Solar Irradiance Interval-Valued Prediction Model with Multi-Objective Optimization of Reliability, Sharpness and Stability," 2023 13th International Conference on Information Science and Technology (ICIST, EI会议), pp. 80-87, 2023.

[17] W. W. Y. Ng, P. Zheng, T. Wang, J. Zhang*(张建军), Y. Liang, H. Zhou, D. Liang, G. Li, and X. Wei, "LSSED: A robust segmentation network for inflamed appendix from CT images," 2023 IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP, CCF-B类会议), Accepted, 2023.

[16] T. Wang, J. Zhang*(张建军), W. Ng, X. Zhang, S. Zhang, C. Nugent, N. Irvine and S. Kwong, "Feature learning based on stacked adversarial autoencoders for time series change point detection," 2023 IEEE 22nd International Conference on Cognitive Informatics & Cognitive Computing (ICCI*CC，EI会议), Accepted, 2023.

[15] T. Wang, W. W. Y. Ng, M. Zhang, X. Zhang, J. Zhang(张建军), M. Deng, "Moisture content prediction of sugi wood drying using deep lstm ae minimizing perturbed error," 2023 IEEE International Conference on Systems, Man, and Cybernetics (SMC, CCF-C类会议), Accepted, 2023.

[14] S. Deng, Y. Suo, S. Liu, X. Ma, H. Chen, X. Liao, J. Zhang(张建军), and W. W. Y. Ng, " MFCSA-CAT: A multimodal fusion method for cancer survival analysis based on cross-attention transformer," 2022 5th International Conference on Computer Information Science and Artificial Intelligence (CISAI 2022, EI会议), 2022.

[13] J. Zhang(张建军), T. Wang, W. W. Y. Ng, W. Pedrycz, S. Zhang and C. D. Nugent, "Minority oversampling using sensitivity," 2020 International Joint Conference on Neural Networks (IJCNN, CCF-C类会议), 2020, pp. 1-7.

[12] J. Zhang(张建军), T. Wang, W. W. Y. Ng, and S. Kwong, "Stochastic sensitivity regularized autoencoder for robust feature learning," 2022 IEEE 21st International Conference on Cognitive Informatics & Cognitive Computing (ICCI*CC, EI会议，最佳论文奖), 2022.

[11] X. Tian, L. Qiu, Q. Li, W. W. Y. Ng, J. Zhang(张建军), S. Kwong, H. Wang, X. Dong, B. Liu, Y. Hu and H. Yu, "Hashing-based undersampling for large scale histopathology image classification," 2022 IEEE 21st International Conference on Cognitive Informatics & Cognitive Computing (ICCI*CC, EI会议), 2022.

[10] J. Zhang(张建军), T. Wang, W. W. Y. Ng, S. Zhang, and C. D. Nugent, "Undersampling near decision boundary for imbalance problems," 2019 International Conference on Machine Learning and Cybernetics (ICMLC, EI会议), 2019.

[9] J. Zhang(张建军), and W. W. Y. Ng, " Stochastic sensitivity measure-based noise filtering and oversampling method for imbalanced classification problems," 2018 IEEE International Conference on Systems, Man, and Cybernetics (SMC, CCF-C类会议), 2018.

[8] Z. Liu, J. Zhang(张建军), and W. W. Y. Ng, "Imbalanced high-frequency number classification based on DSUS," 2018 International Conference on Machine Learning and Cybernetics (ICMLC, EI 会议), 2018.

[7] Y. Chen, J. Zhang(张建军), and W. W. Y. Ng, "Loan default prediction using diversified sensitivity undersampling," 2018 International Conference on Machine Learning and Cybernetics (ICMLC, EI 会议), 2018.

[6] S. Zhang, W. W. Y. Ng, J. Zhang(张建军), and C. D. Nugent, "Human activity recognition using radial basis function neural network trained via a minimization of localized generalization error," International Conference on Ubiquitous Computing and Ambient Intelligence (UCAmI, EI会议), 2017.

[5] W. W. Y. Ng, Y. Zhang, J. Zhang*(张建军), "Bsmboost for imbalanced pattern classification problems," 2017 IEEE International Conference on Systems, Man, and Cybernetics (SMC, CCF-C类会议), 2017.

[4] Y. Chai, J. Zhang(张建军), W. W. Y. Ng, "Weighted ensemble of diversified sensitivity-based undersampling for imbalanced pattern classification problems," 2017 International Conference on Machine Learning and Cybernetics (ICMLC, EI会议), 2017.

[3] W. W. Y. Ng, J. Li, J. Zhang(张建军), Q. Wu, J. Li, "Visual words selection for human action recognition using rbfnn via the minimization of L-GEM," 2017 International Conference on Wavelet Analysis and Pattern Recognition (ICWAPR, EI会议), 2017.

[2] T. Chen, T. Wang, W. W. Y. Ng, J. Zhang(张建军), "Feature weighting for rbfnn based on genetic algorithm and localized generalization error model," 2017 IEEE International Conference on Internet of Things (iThings) and IEEE Green Computing and Communications (GreenCom) and IEEE Cyber, Physical and Social Computing (CPSCom) and IEEE Smart Data (SmartData), 2017.

[1] J. Liao, J. Zhang(张建军), W. W. Y. Ng, "Effects of different base classifiers to Learn++ family algorithms for concept drifting and imbalanced pattern classification problems," 2016 International Conference on Machine Learning and Cybernetics (ICMLC, EI会议), 2016.

1． 吴永贤，刘政锡，张建军，基于代价局部泛化误差的不平衡问题的分类方法，2022-3-29，中国，ZL201910267769.2

2． 吴永贤，丘林，田星，张建军，王婷，余洪华，一种针对组织病理学图像的哈希样本平衡癌症标注方法，2023-12-19，中国，ZL202110228166.9

3.    吴永贤，莫振尧，张建军，基于随机敏感度的知识迁移方法，2024-05-10，中国，ZL202210202516.9 

o 2017-06至今，曾多次赴英国阿尔斯特大学进行学术访问与项目合作，均由外方学校全额资助

o 2018-2019年，曾赴香港城市大学、加拿大阿尔伯塔大学、英国利兹大学、西班牙哈恩大学等进行学术访问与交流，并曾前往日本参加国际学术会议

o 2019-10至2020-10，曾受国家公派留学基金项目资助，赴加拿大阿尔伯塔大学进行联合培养

指导21级本科生邓同学本科期间发表中科院1区Top期刊论文1篇，CCF-B类会议论文1篇，EI检索会议论文1篇，主持大学生创新创业训练计划项目1项。其它本科生或研究生同学在课题组期间均发表至少EI检索会议论文1篇或SCI期刊论文1篇。

目前招收专业硕士研究生，对机器学习、深度网络理论与应用研究感兴趣的同学可提前与我联系，报考我的硕士研究生（jianjunzhang@scau.edu.cn）